The study was carried out to determine the economic value of forest conserved by local community for carbon sequestration in the Humbo District, Ethiopia. The contingent valuation method (CVM) using the double bounded bivariate probit econometric method was employed to estimate WTP for sustainable forest management. Household survey was randomly conducted in 218 res pondents purposively selected from three forest development cooperatives. The bivariate probit model was run to estimate mean WTP and to identify the determinant factors for farmers’ WTP for forest conservation. Thus, the mean WTP with covariates was estimated to be 104.38 Ethiopian Birr (ETB) and 55.73 ETB1 per year for the initial bid and for the follow-up bid amount, respec tively. The result also indicated that respondents’ level of education, marital status, years of membership in the cooperatives, second bid amount, distance of residence from forest of interest, and net family income were significantly related to WTP for forest conservation. The study showed that even the poor households were willing to pay the average values in terms of cash contribution to maintain the forest management responsibility following the withdrawal of the NGO. In conclu sion, whereas CVM can be applied to determine WTP for forest conservation, local people recognize and give value to the environmental services of the forest and are willing to maintain those benefits. The study also indicates the potential for sustainable forest management through com munity-based approach.
The world forest covers about 4 billion hectares of land. The forest cover of Africa was close to 674 million hectare out of which 73 million hectare was the share of East Africa. During the same period, Ethiopia also had a forest cover of 12 million hectare which almost covered 11% of the land [
Forest resources are the most productive ecosystems providing a wide range of important ecological functions, life supporting and other services. Forestry can play significant role in boosting economic development of agrarian countries like Ethiopia. However, the contribution of forestry sector to the country’s GDP in promoting the whole economy as compared to agriculture sector has been very low (5.5%). The reason was attributed to policy failure and market imperfection resulting from lack of measurement and valuation of the non-marketable goods and services obtained from forest resources [
As in the rest parts of developing countries, the response of Ethiopia to the challenge of climate change has considerably been increased over the years. Ethiopia is a signatory to Kyoto protocol in 2005 and parties to the convention. One of the remarkable roles played by the country was the launching of Humbo Community Assisted Natural Regeneration Aforestation/Reforestation (A/R) implemented under Clean Development Mechanism (CDM) both to ensure sustainable development and emission reduction. Humbo project is the second largest registered carbon project in the world next to China’s CDM project [
The project has a potential to sequester a total of 880,295 tons of carbon dioxide equivalent (CO2 equivalent tons) throughout its crediting period (30 years). But, World Bank has signed purchase agreement only for 165,000 t CO2e sequestered over the first ten years period, from which has a value of $726,000.
The project has been implemented by World Vision Ethiopia with the financial and technical support from World Vision Australia in collaboration with the government of Ethiopia and local community. World Bank has also been providing the required technical support and community capacity building fund. But, World Vision Ethiopia has a plan to handover the project to Forest development cooperatives at the end of year 2014. Thus, the community is expected to fully handle the overall resource management under sustainable basis. Although the forest production (Forest management activities) and transaction costs will be minimum in the years to come but, the community is expected to cover any costs incurred to run the business afterwards. Hence, this research paper gave emphasis to assess community’s willingness to pay (WTP) to maintain forest management for the benefit of future carbon sequestration and other environmental co-benefits in the absence of World Vision Ethiopia throughout the project life [
The study was conducted in Humbo Woreda, Wolaita Zone, Southern Nations Nationalities and Peoples Regional State (SNNPRS), South Western of Ethiopia. Humbo is one of the twelve rural districts in Wolaita Zone. The total population of the district was 132,780. The district has 36 local level Administrative (Kebeles) out of which 35 is rural and 1 urban Administration covering a total land area of 97,363 ha [
The sampling frame for survey included those households that are legally organized as forest development cooperatives to manage the forest of interest. A two stage sampling procedures was employed to select the sample households in the study area. In the first stage, three representative Cooperatives out of seven were purposively selected on the basis of their accessibility and representativeness (Abela Longena, Hobicha Bada and Abela Shoya. In the second stage, Proportional sampling technique was applied to draw samples from the population. Thus, 10% of the households from each cooperative were included in the sample i.e. 85, 84 and 49 households were selected respectively from each Cooperatives using systematic random sampling technique irrespective of their sex, social and economic status. This would thus give a total of 218 sample households for the survey.
The survey was conducted to generate empirical data through estimating individual’s stated WTP to manage the forest of interest. Household survey was conducted to gather qualitative and quantitative data from randomly selected individual respondents. A double-bounded elicitation format was employed.
The payment situation was well described in the questionnaire and the respondents were presented with the WTP question that included one of five different starting amounts (five bid levels) in Birr (10, 20, 30, 40 and 50) which was randomly assigned. If the respondents answer the first question affirmatively, then the amount was increased (doubled) otherwise, it was decreased (halved). The payment vehicle used was cash payment on per year payment basis. Key informants were also asked to assess the prospect of community in view of forest management.
Model specification: Contingent valuation method was applied to elicit the people’s willingness-to-pay for the environmental change (improved forest ecosystem through carbon sequestration). This method is particularly applicable in a situation where market information about people’s preference is absent. Thus, this study adopts the model developed by Cameron and Quiggin and aims at identifying the true WTP of the forest development cooperatives and assessing determining factors using single and bivariate probit model. Accordingly single bound probit model takes the following form [
where
Yi = ith respondent’s true unobserved point valuation for the environmental resource in question,
β = a coefficient for X,
ti = the offered threshold, assigned arbitrarily to the ith respondent,
I = discrete response of a respondent for the WTP question (1 = yes, 0 = no),
εi = unobservable random component distributed N (0, s),
Xi = observable attributes of the respondent.
Bivariate Probit Model: Bivariate normal probability density functions are the most familiar bivariate distributions employed commonly by statisticians; they allow for a non-zero correlation, whereas the standard logistic distribution (logit model) does not [
The model takes the following form [
The jth contribution to the Likelihood function is given as
This formulation is referred to as the bivariate discrete choice model,
where
m = mean value for willingness to pay,
YY = 1 for a yes-yes answer, 0 otherwise, NY =1 for a no-yes answer, 0 otherwise, etc.
And the jth contribution to the bivariate probit Likelihood function becomes
where:
r = correlation coefficient,
s = standard deviation of the errors.
The general model can be readily estimated using standard packaged bivariate probit algorithms using STATA (version 10) software.
Estimation Techniques: A dichotomous choice contingent valuation method with follow-up questions was used to elicit the mean WTP of the respondents to observe the changes in the forest of interest. The dependent variable in the model is a dummy variable, which assumes either 0 or 1. The use of dichotomous choice questions with follow-up bids implies that the response for the second question is endogenous to that of the first. This means that, the model cannot be estimated using the ordinary probit/logit model. Thus, bivariate probit model, which simultaneously estimate the two equations, was employed in order to minimize the misrepresentation that might be happen due to the endogenous characteristics of the second response.
Households Social, Economic, Environmental and Demographic Characteristics
The respondents’ age ranges from 17 to 90 and a significant proportion of them (81.7%) are within the active labor force (
Variable | Mean | Std. Dev. | Min | Max |
---|---|---|---|---|
Sex of respondent (SexR) male = 0 | 0.1972 | 0.3988 | 0 | 1 |
Age of respondent (AgeR) | 40.577 | 13.294 | 17 | 90 |
Family size of respondent (FamSR) | 6.4311 | 2.6181 | 1 | 11 |
Education level of respond. = (EduR), attend form.edu = 1 | 0.4678 | 0.5001 | 0 | 1 |
Marital status of respondent (MarR) married = 1 | 0.8853 | 0.3193 | 0 | 1 |
Years of membership (YearM) | 4.0412 | 1.0789 | 2 | 6 |
Distance from forest site (DistR) | 0.2889 | 0.4543 | 0 | 1 |
Environmental know of respondent (EnAR) | 0.7981 | 0.4022 | 0 | 1 |
First bid amount (Fbid) | 29.770 | 14.189 | 10 | 50 |
Second bid amount (Sbid) | 36.926 | 14.770 | 5 | 60 |
Net income (Ntincome) | 4201.5 | 1616.3 | 2000 | 8720 |
Maximum willingness to pay (MWTP) | 48.096 | 27.988 | 0 | 150 |
Source: Survey result, 2012.
which on average leads to high dependency ratio of 5.07. The average family size of the sampled households is 6.43 with a range of 1 to 11 family members. About 88% of the respondents were married, while the remaining 12% were unmarried and these includes widows and divorced heads of household. As far as the education level of the respondents is concerned, 53% of them are illiterate. This indicates that most of the respondents had no access to formal education.
Distance is dummy variable 1 for residents living proximate to forest of interest 0 other wise and referring to the respondent’s location from forest of interest. Thus, the survey result indicated that 71% of the respondents residing proximate to forest of interest. Number of years of membership is also continuous variable and refers to number of years that the respondents have been staying in the cooperatives as a member. The time respondents became cooperatives member was vary from 2 to 6 years having a mean of 4.04 years on average. Accordingly, the study indicated that all of the respondents were member for two and more years in the forest development cooperatives (
Income: is continuous variable indicating the net amount of income earned by respondents from various sources in birr value per annum. Thus, the study result showed that the community entertained different sources of income although limited in number. The major sources of income involve farming, off-farm and natural resources. In order to get detailed and valid information gross income of various sources calculated for the past twelve months. Then after, net income computed by deducting different costs incurred from gross income. Accordingly, the minimum net annual family income found to be 2000 while the maximum was 8720 ETB. Based on this approach, mean value of net annual income from various activities was estimated to be 4201 ETB per household (
Environmental Knowledge: this variable has a positive relationship with respondents WTP to manage the forest. The more the environmental knowledge means the better the respondents know environmental benefits and this could be expressed through contribution. Thus, 79.8% of the respondents have environmental knowledge of their locality3 (
Bids Amount: Refers to the variable with different threshold values offered randomly to be responded for accordingly. Thus, it was assumed that the higher the threshold value proposed, the less willing the respondent to pay for the resources in question. So, it is expected to have negative sign. Five threshold values offered as starting bid i.e.10, 20, 30, 40 and 50 ETB). Thus, the offered minimum first bid amount is 10 ETB while the maximum is 50 ETB with the average starting bid amount is 29.77 ETB. The second bid amount is 5, 10, 20, 30, 40, 50 and 60 ETB with mean value of 36.92 ETB (
Environmental Situation of the Study Area
Before forestry project there were major environmental problems. The major environmental problems includes; deforestation, soil erosion and climatic variability. Accordingly, in relation to the depletion of forest resources (deforestation) 27% respondents expressed that they had medium knowledge while 71% had high knowledge of deforestation and the remaining 2% had no knowledge. About 61% of the respondents had high knowledge of soil erosion problem. About 37% of the respondents had medium knowledge while only 2% of the respondents had no knowledge of soil erosion. From climatic change and variability problem point of view, only 2% of respondents had no knowledge, 46% medium while the remaining 52% had high knowledge (
As far as environmental problem of the study area is concerned, various factors have different level of severity status to impose at particular locality. In this respect, 56% of the respondents indicated that deforestation was a big challenge followed by soil erosion 42%. As a result of deforestation; environmental problems like climate variability (29%), depletion of water sources (29%) and loss of biodiversity (45%) ranked third, fourth and fifth order of severity level respectively (
Following the commencement of the Project, various environmental benefits have been appearing due to project conservation practices (
Environmental problems | Status of understanding the problem (%) | Total | ||
---|---|---|---|---|
No | Medium | High | ||
Deforestation | 2 | 27 | 71 | 100 |
Soil erosion | 2 | 37 | 61 | 100 |
Climate variability | 2 | 46 | 52 | 100 |
Source: Survey result, 2012.
Environmental problem | Order of environmental problem (level of severity) | ||||
---|---|---|---|---|---|
1st (%) | 2nd (%) | 3rd (%) | 4th (%) | 5th (%) | |
Deforestation | 56 | 18 | 9 | 14 | 22 |
Loss of biodiversity | 2 | 14 | 17 | 22 | 45 |
Climate change | 12 | 18 | 29 | 20 | 3 |
Soil erosion | 17 | 42 | 18 | 15 | 7 |
Depletion of water sources | 13 | 8 | 27 | 29 | 23 |
Total | 100 | 100 | 100 | 100 | 100 |
Source: Survey result, 2012.
Environmental benefits | Rank (% of respondents) | ||||||
---|---|---|---|---|---|---|---|
1st | 2nd | 3rd | 4th | 5th | 6th | 7th | |
Improved water sources | 10 | 17 | 17 | 19 | 13 | 10 | 13 |
Improved microclimate | 43 | 23 | 20 | 8 | 4 | 2 | 1 |
Reduced soil erosion | 22 | 28 | 22 | 10 | 14 | 3 | 2 |
Improved biodiversity | 1 | 5 | 12 | 12 | 19 | 24 | 28 |
Created job opportunity | 5 | 2 | 6 | 14 | 21 | 29 | 22 |
Improved fuel wood sources | 11 | 10 | 4 | 15 | 15 | 18 | 26 |
Improved sources of grass | 8 | 15 | 19 | 22 | 14 | 14 | 8 |
Total | 100 | 100 | 100 | 100 | 100 | 100 | 100 |
Sources: Survey result, 2012.
The study result indicated that 100% of the respondents said “yes” to the positive impacts of rehabilitation effort. Hence, the most frequently mentioned environmental benefit was the improved microclimate (43%) of the respective area and followed by reduced soil erosion (28%). The third important factor was improved availability of grass (19%) to feed their livestock, which also positively impacted the livelihood of respective community through sale of grass and increased milk production. Moreover, increased water availability (19%), creation of job opportunity (21%) and improved biodiversity (24%) ranked fourth, fifth and sixth respectively while, fuel wood sources ranked the last (
The community banned from fuel wood collection and cutting of live trees for other purposes due to leakage problem. But, during thinning operation communities have a change fetch twigs and branches for household consumption. Moreover, they also used fuel wood from their own home yard. On top of this, the project also provide tree seedlings to community for free as a buffer plantation for further use.
Descriptive Statistics for Double Bounded Dichotomous Choice Questions
The average amount of the 1st bid is 29.77 ETB per year but the value increased to 36.93 ETB for the 2nd bid amount (
About 91% of the 44 respondents of the 10 ETB initial bid accepted both 1st and 2nd bids i.e. 10 and 20 ETB and about 76.6% of the 43 respondents of the 50 ETB with initial bid accepted both 1st and 2nd bids (50 and 60 ETB). This indicates that as the 1st bid get increased the number of voters decreased. Generally, it is possible to note that as the initial bid gets higher the share of “Yes” response for the initial bid decreases. The result of
Acronym | Description | Mean | St. D | Min | Max |
---|---|---|---|---|---|
t1 | Exogenous threshold4 (t1) for the first question | 29.77 | 14.19 | 10 | 50 |
t2 | Endogenous threshold (t2) for second question | 36.93 | 14.77 | 5 | 60 |
I1 | Discrete response of the 1st question (1 = yes, 0 = no) | 0.91 | 0.283 | 0 | 1 |
I2 | Discrete response for 2nd question (1 = yes, 0 = no) | 0.83 | 0.380 | 0 | 1 |
Source: Survey result, 2012.
Discrete response | Freq. | Mean | St. Dev | Min | Max | |
---|---|---|---|---|---|---|
Yes-Yes (YY) response for both questions | 161 | 0.73 | 0.440 | 0 | 1 | |
Yes-No (YN) response for both questions | 36 | 0.17 | 0.372 | 0 | 1 | |
No-Yes (NY) response for both questions | 17 | 0.08 | 0.269 | 0 | 1 | |
No-No (NN) response for both questions | 4 | 0.02 | 0.135 | 0 | 1 | |
Total | 218 | 1 | ||||
Source: Survey result, 2012.
Multicollinearity: multicollinearity is referring to the existence of a “perfect” or “exact”, linear relationship among some or all explanatory variables of a regression model [
The formula of VIF can be expressed as:
where,
Finally, after passing through aforementioned serious of steps, the results of explanatory variables were presented in table below (
The result indicated that, all explanatory variables are not significant while the overall model is significant at 5% level. As it was expected, although distance of the respondents and the offered first bid insignificant but negatively will affect their WTP for the resources in questions. Moreover, in contrast to the expectation; marital status, year of being membership and environmental knowledge are found insignificant and also negatively affected their WTP to manage the forest of interest (
Mean Willingness to Pay (Mean WTP) for Carbon Forestry Project Management and Estimation of Explanatory Variables from Double Bounded Dichotomous Choice Question
The mean willingness to pay (μ) was calculated using the formula [
where: α = a coefficient for the constant term,
β = a coefficient for the amount of the bid that the family was asked to pay.
From the summarized responses for the first and the second bids, a total of 436 usable responses were obtained.
Variables | Collinearity statistics | Coefficient correlations | ||||||||
---|---|---|---|---|---|---|---|---|---|---|
VIF | Distance | Family size | Environ. know | Education | Sex | Income | Year of mem. | Age | Marital status | |
Distance | 1.116 | 1 | ||||||||
Family size | 1.252 | −0.012 | 1 | |||||||
Environ. know | 1.026 | −0.001 | −0.072 | 1 | ||||||
Education | 1.145 | 0.015 | −0.070 | −0.024 | 1 | |||||
Sex | 1.169 | −0.090 | −0.119 | 0.053 | 0.137 | 1 | ||||
Income | 1.026 | −0.186 | 0.059 | 0.001 | −0.052 | −0.036 | 1 | |||
Year of mem. | 1.038 | 0.200 | −0.134 | 0.127 | −0.030 | −0.021 | −0.009 | 1 | ||
Age | 1.247 | −0.115 | −0.298 | 0.043 | 0.305 | 0.018 | 0.017 | 0.034 | 1 | |
Marital status | 1.276 | 0.026 | −0.283 | 0.070 | −0.060 | 0.330 | 0.079 | 0.068 | −0.074 | 1 |
Source: Survey result, 2012.
Variables | Probit coefficients | P > /Z/ | SD error |
---|---|---|---|
Sex of respondent (SexR) | 0.0485278 | 0.885 | 0.334660 |
Age of respondent (AgeR) | 0.0116001 | 0.325 | 0.011779 |
Family size of resp. (FamSR) | 0.0035174 | 0.941 | 0.047666 |
Education level of resp. (EduR) | 0.0798405 | 0.741 | 0.241491 |
Marital status of resp. (MarR) | −0.509332 | 0.311 | 0.502486 |
Years of membership (YearM) | −0.0209681 | 0.845 | 0.107086 |
Distance from forest site (DistR) | −0.0112761 | 0.966 | 0.261984 |
Environmental know. (EnAR) | −0.174373 | 0.589 | 0.322713 |
First bid amount (Fbid) | −0.0045734 | 0.617 | 0.009149 |
Net income (Ntincome) | 0.0000344 | 0.585 | 0.000063 |
_Constant | 1.525866 | 0.118 | 0.975572 |
Number of observation | 218 | ||
Wald Chi2 (10) | 3.89 | ||
Pseudo R2 | 0.9523 | ||
Prob > Chi2 | 0.0263** | ||
Log pseudo likelihood | −62.81106 |
Source: Survey result, 2012; Note: ***, **, * indicates significance level at 1%, 5% and 10%.
Double-bounded contingent valuation model is used to estimate the mean willingness-to-pay and its determinants. There are two options of independent models which can be used to estimate mean WTP. The models are bivariate model with no covariates i.e. WTP checked against the offered amount and bivariate model with covariates i.e. WTP against age, gender, education, family size, distance from forest of interest, marital status, years of being cooperatives membership, environmental awareness, offered amount and family net income. Thus, before deciding on which model to apply, it seems important to compare their results which would help to capture the true behavior of people that expressed through their preferences. Thus, the result from the second model was preferred for it uses covariates to run the model (
Variables | Probit coefficient | P > /Z/ | SD Error | |||||
---|---|---|---|---|---|---|---|---|
Model-I | Model-II | M-I | Model-II | Model-I | Model-II | |||
Sex of respondent (SexR) | 0.0861159 | 0.1438551 | 0.794 | 0.607 | 0.330000 | 0.2796774 | ||
Age of respondent (AgeR) | 0.013639 | −0.0031993 | 0.244 | 0.741 | 0.011701 | 0.0096613 | ||
Family size of respondent | −0.0002078 | 0.0265806 | 0.997 | 0.564 | 0.047457 | 0.0460547 | ||
Education level (EduR) | 0.1081521 | 0.6739087 | 0.653 | 0.005*** | 0.240503 | 0.2385764 | ||
Marital status (MarsR) | −0.4990871 | 0.9732873 | 0.311 | 0.005*** | 0.492557 | 0.3492515 | ||
Years of membership | −0.0326813 | −0.274606 | 0.768 | 0.002*** | 0.110678 | 0.0897633 | ||
Distance from forest site | 0.0272502 | −1.201628 | 0.917 | 0.000*** | 0.261239 | 0.2461782 | ||
Environmental Know | −0.2023155 | 0.3056021 | 0.524 | 0.283 | 0.317381 | 0.2845043 | ||
First bid amount (Fbid) | −0.0143836 | NA | 0.635 | NA | 0.009223 | NA | ||
Second bid amount (Sbid) | NA | −0.022867 | NA | 0.005*** | NA | 0.0081606 | ||
Net income (Ntincome) | 0.000033 | 0.000176 | 0.604 | 0.014** | 0.000063 | 0.0000716 | ||
_Constant | 1.501364 | 1.274501 | 0.11 | 0.115 | 0.938756 | 0.8096034 | ||
Number of observation | 218 | |||||||
Wald Chi2 (20) | 51.20 | |||||||
Rho (p-value) | 0.424529 | |||||||
Prob > Chi2 | 0.0001*** | |||||||
Log pseudo likelihood | −135.30805 | |||||||
Chi2 (1) | 3.69662 | |||||||
Source: Survey result, 2012; Note: ***, ** and * indicate significance level at 1%, 5% and 10% respectively.
The quantity Chi2 (𝜒2) illustrated (
Family size, education level, marital status, years of membership, distance of residence from forest site, environmental knowledge and the net family income did not significantly affect the WTP. In contrary Applying equation (5) above, the coefficients of constant term divided to the coefficient of offered amount to estimate the mean willingness to pay for forest management. Accordingly, the double bounded bivariate probit estimate (with covariates) of the mean willingness to pay ranged from 104.38 ETB to 55.73 ETB for the initial bid (Fbid) and for the follow up second bid amount (Sbid) respectively. Generally, this figure was much higher than the mean willingness to pay amount from the open-ended question (Maximum WTP) which was 48.0963 ETB. Also the mean WTP of single bounded probit estimate was highly exaggerated than that of the double bounded estimate. Mean WTP will be overestimated if a cumulative density function estimated from dichotomous choice data has an unrealistically fat right-hand tail. If a cumulative density function estimated from dichotomous choice data has an unrealistically fat right-hand tail, mean WTP will be overestimated [
Determinant Factors Affecting Respondents WTP
Furthermore, respondents’ exposed to various socio-economic and demographic situations which will influence their mean willingness-to-pay. Following the results of bivariate probit analyses, the variables that were expected to influence the respondent’s willingness to pay for managing forest resources after taking over from World Vision Ethiopia (
To see the marginal effect of each of ten (10) independent variables on individual’s WTP for the forest of interest the bivariate probit model was run (
Membership of Forest Development Cooperatives (YearM): Years of being cooperatives Membership of the respondents is negative and significant at 1%. This indicated that respondents have a claim for a benefit share from the sale of carbon credit at individual basis. Due to this grievance they negatively react to pay for the respective resource management. As evidence to this, keeping other factors constant one year additional as being
Variable | Marginal effect | Variable | Marginal effect |
---|---|---|---|
Sex of respondent (SexR) | 0.0315871 | Years of Membership | −0.0481639 |
Age of respondent (AgeR) | 0.001007 | Distance from forest site | −0.2624886 |
Family size of respondent | 0.004285 | Environmental Know | 0.0371538 |
Education level (EduR) | 0.1195714 | Net Income | 0.0000322 |
Marital status (MarsR) | 0.2157159 | Second bid amount (Sbid) | −0.0037063 |
Source: Survey result, 2012.
member of forest cooperative resulted in declining of WTP by −0.0481 marginal effects (
Bids Amount (Bids): The second bid amount of the respondents is found to be negative and significant at 1% (
Distance of the Household from Carbon Sequestration Forestry Project Site (DistR): There spondent’s distance from forest of interest is negative and significant at 1% to influence the respondents’ WTP. The result showed that, keeping other factors constant, one more unit of increment in respondent’s distance from the forest of interest will result in declining of WTP by −0.2624886 marginal effect (
Moreover, variables like Education and Marital status of the respondents are also positive and significant at 1%. Keeping other variables constant, when one of uneducated respondents promoted into formal education status the WTP increased by 0.1195714 marginal effect. The determinant factor; net family income is also positive and significant at 5% in influencing respondents’ WTP (
It is possible to conclude from the result that the respective communities are willing to pay to manage carbon forestry project despite the fact that there are various pressing problems they have been facing and murmuring at lack of revenue from the sale of carbon credit. Thus, this further suggests that individuals’ livelihood needs to be addressed and equitable benefit sharing from carbon credit scheme should also be given emphasis in order to ensure project sustainability. Furthermore, the conflict between community and wild animals needs thorough attention, thus planning on how to resolve the conflict between them is indispensable.
Moreover, it is quite understandable from the result that; designing appropriate sustainable development plan and establishing of forest cooperatives is not a mere solution. For the project to be sustainable, establishing of Forest Union5 and promoting its management capacity is a crucial measure. Currently, the cooperatives are poorly equipped and understaffed especially in terms of skilled manpower in the area of financial management, Archive handling and forestry technical background. Empowering community’s management capacity is so crucial not only to generate sufficient revenues from the sale of carbon credit but also to helps to ensure project sustainability.
Insignificant Explanatory Variables
Independent variables which were expected to have impact on individual’s WTP for the forest of interest in the study area were included in the model. The explanatory variables like sex, age, family size and environmental knowledge of the respondents found insignificant to influence respondents’ WTP for the management of forest of interest. As it was expected, sex of the respondent is positive for male but, insignificant in influencing individual’s WTP. This revealed that although males are more WTP for the forest of interest than their counterparts but, their influence remains insignificant. Thus, this illustrate that both sex have better access to forest management information and decision making process. Although the respondents’ environmental knowledge appeared as it was expected to positively influence individual’s WTP for the forest of interest, but its impact found to be insignificant. The explanatory variables age and family size of the respondents’ appeared as opposed to the expectation. The assumption for age was positive that, as the age of respondents get increased the WTP for the resource also increased. But, the survey result indicated that; as age of the respondents get increased their WTP for the forest of interest get decline. Hence, the younger community members are more interested to pay for the management of forest than the older respondents (
The bivariate probit Model provides information about the behavior of the variables that determine peoples WTP. Thus, a significant negative relationship is found between Years of being member of forest development cooperative and WTP (p-value < 0.01). This means that the higher the years of being member of cooperatives the lesser the probability of answering yes to WTP questions. The lesson here is that, although the cooperatives benefited from the sale of carbon credit yet, no money directly channeled into individuals’ pocket. This is so because, although the cooperatives have a business plan of their own the focus is only given to invest on common infrastructure like grain mills that intends to benefit the entire community being member or non member. Thus, individuals’ interest should also need to be addressed in providing appropriate dividend from carbon revenue.
There is also a significant negative relationship between second bid and WTP (p-value < 0.01), indicating that as the magnitude of the offered amount increases, it is less likely that individuals will be willing to pay the offered amount (
The fact that the coefficients for first bid (Fbid) and second bid (Sbid) are negative and net income (Ntincome) is positive, i.e. the higher the income of respondents by one unit the higher the probability of answering yes to the WTP question, this validates the model in accordance with theoretical expectations. Moreover, a significant positive relationship is also found between education and WTP (p-value < 0.01) and marital status of the respondents and WTP (p-value < 0.01), i.e. keeping other factors constant the addition of one more unit from illiteracy to formal education status in household education will positively contribute to WTP. From the result, it can also be realized that keeping the influences of other factors constant, every extra year of schooling increase the respondents’ WTP by 0.1195714 marginal effect (
Moreover, the variable marriage also indicated that when one respondent shift from single (unmarried) status to married status it resulted in increased probability of answering yes to the WTP question. As expected, the significant negative relationship is found between distance that the respondents are living from the forest of interest and WTP (p-value < 0.01), i.e. indicating that the farther the households from the forest of interest, the less willing they are to pay to manage the forest. Thus, such a community members need to be thoroughly addressed through extension work to engage them in forest management and overall decision making process. As the survey result indicated, the first question (Fbid) produced higher estimates of the mean WTP than the second question (Sbid). It is clear from the result that, the respondents become more aware of and thus make adjustment to the amount of money they have willing to pay for the second bid offered. This means that WTP estimates for the second question are preferred to the estimates for the first question. This is consistent with research on the contingent valuation debate presented by American Economic Association which argues that, the second follow-up questions helps to ensure that respondents understood the choice they were being asked to make and to discover the reasons for their answer [
Aggregation of Benefits
Before conducting benefit aggregation it was advised [
If the bivariate probit model is estimated on a dichotomous choice CV question with a follow up and the parameter shows that either the mean, or variance or both differ between the initial bid-price and the follow up, hence it is the mandate of the researcher to decide on which estimates to use to calculate the WTP measure [
The sample mean of the WTP estimates used to derive an aggregate measure of welfare change for the entire population from which the survey sample is drawn and finally multiplied by the total population [
Cost of Forest Management
After the withdrawal of World Vision Ethiopia, Forest Development Cooperatives are expected to take over the overall project management. Majority of project activities like seedling production and plantation was almost completed right at this time unless silvicultural operations need to be done regularly. Thus, during the last six years a total of 799,751 USD costs have been incurred to successfully accomplish the aforementioned project activities. After taking over the project from World Vision Ethiopia, the cooperatives will be expected to incur a cost of 5.5% from carbon revenue as carbon reversals6 and operation costs7. Therefore, from 2014-2017 on average the overall estimated cost for execution of carbon reversals and field operation is amounting to 180,532 ETB (10,000 USD) per year. If the anticipated forest damage will not occur, the cooperatives do not liable to incur carbon reversal costs.
Comparison of WTP and Cost of Forest Management
As per the survey result, in aggregate the community (three Kebeles) willing to pay 121,503 ETB per year to maintain forest management. If the same mean WTP is extrapolated over the whole cooperative members (4975 members) the community WTP 277,256.80 ETB per year to manage the forest of interest. Thus, the net benefit which the community will be expected to use as a welfare improvement is accounted to 96,724.80 ETB per year. Moreover, the community also has an opportunity to get additional revenue from the sale of carbon credit which accounted to 726,000 USD until 2017 (
Kebeles | Population size | Mean WTP (ETB) | Total WTP (ETB) |
---|---|---|---|
Abela Longena | 851 | 55.73 | 47,426.23 |
Hobicha Bada | 840 | 55.73 | 46,813.65 |
Abela Shoya | 489 | 55.73 | 27,251.97 |
Sample total | 2180 | 55.73 | 121,491.40 |
Population total | 4975 | 55.73 | 277,256.8 |
Source: Survey result, 2012.
while they are eager to share the remaining 74% on individual basis. In contrast, cooperatives leaders neglect individuals’ interest and generally preferred to reinvest on construction of common infrastructures like grain mill and grain store which will benefited the entire community regardless of being member or non member of forest development cooperatives.
To conclude with, total project implementation and Carbon compliance Costs that will be incurred by cooperatives from 2014 until 2017 amounting to a total of 40,000 USD9, which annually on average for the coming four years is about 10,000 USD (180,532 ETB). Thus, in comparing the cost of forest management, it was found that the society will be able to save net 96,724.80 ETB as a welfare improvement each year from own contribution as expressed in their WTP. But, if the 26% (378,629.80 ETB) contribution from carbon revenue will be disbursed to welfare improvement, the society could be able to save a net benefit of 475,354.60 ETB per year. Thus, this amount will help them to run the project under sustainable basis in the absence of World Vision.
The Forest Development Cooperatives signed sub-Emission Reduction Purchase Agreement (ERPA) with The World Bank to deliver the amount agreed on10 through project life, 30 Years. Thus, the annual revenue from the sale of carbon credit computed by multiplying the annual amount of contracted Emission Reduction (ER) by 4.4 USD under constant market price (
The Prospect of Community in Forest Management: Respondents’ General Comment
At the end of the interview key respondents were encouraged to freely comment on the overall aspect of forest management and the anticipated situation after World Vision Ethiopia hand over the project to community. This investigation is so important to see the level of their awareness about the project, sense of ownership, the concern they have, to indicate the way forward and to investigate their general recommendation to World Vision, government and the entire community.
As per the survey result 66.66% of the key respondents revealed that they are well capable, better equipped and have good sense of ownership. The remaining 33.33% of respondents replied that, following the withdrawal of World Vision Ethiopia; there is a likely that the forest will be exposed to exploitation due to various reasons. They indicated that, corruption (power abuse, lack of transparency and money confiscations by cooperative leaders) and conflict between wild animals and human (33.33%) are the most pressing challenges. The other dimension of challenge is lack of interest to protect forest as World vision did. The other concern was insufficient technical and legal support from respective government and lack of awareness among non-members (
Reporting Year | Period | Annual amount of contract ER to be transferred | Total amount of revenue (USD) | Cumulative amount of contract ER to be transferred (Co2 ton equivalent) |
---|---|---|---|---|
1st | 2009 | 7769 | 34,183.6 | 7769 |
2nd | 2010 | 11,117 | 48,914.8 | 18,886 |
3rd | 2011 | 14,900 | 65560 | 33,786 |
4th | 2012 | 17,398 | 76551.2 | 51,184 |
5th | 2013 | 19,365 | 85206 | 70,549 |
6th | 2014 | 21,049 | 92615.6 | 91,598 |
7th | 2015 | 22,627 | 99558.8 | 114,225 |
8th | 2016 | 24,204 | 106497.6 | 138,429 |
9th | 2017 | 26,571 | 116912.4 | 165,0001611 |
Grand total | 165,000 | 726,000 |
Source: World Vision Ethiopia, 2012.
Respondent’s view | Frequency | % |
---|---|---|
Well established sense of ownership and thus, there is anticipated challenges | 8 | 66.66 |
Although there is improved sense of ownership but there will be an anticipated challenges which negatively impacted the forest of interest | 4 | 33.33 |
Total | 12 | 100 |
Source: Survey result, 2012.
Sources of anticipated challenges | Frequency | % |
---|---|---|
Corruption (lack transparency by coops leaders) | 2 | 16.68 |
Damage by Wild animals to human being and their produce | 4 | 33.33 |
Fire damage by illegal wild honey extractors and protection against wild animals | 1 | 8.33 |
Lack of commitment to protect forest from encroachment | 3 | 25 |
Lack of technical and legal support from government | 1 | 8.33 |
Lack of awareness by non cooperative members | 1 | 8.33 |
Total | 12 | 100 |
Source: Survey result, 2012.
Finally, the respondents provided important and valid comments (
In this study, CVM was used to elicit households’ willingness to pay for managing carbon sequestration forestry project in Humbo Community Assisted Natural Regeneration Forestry project of Woliata Zone, Humbo Woreda.
Respondents were asked about their WTP per year to manage project for the coming ten years. Thus, the respondents expressed their WTP average payment of 104.38 ETB and 55.73 ETB per year for first and second bids respectively. This model could be found more accurate in evaluating the respondents’ true preferences or unobserved behavior [
The estimation of bivariate probit model using covariates indicated that the year of being membership of cooperatives and the offered second bid amount were the variables which negatively and significantly influenced WTP at 1% significance level. This result showed that those individuals who had been a member for longer time reacted negatively due to limited access to benefit sharing from the sale of carbon revenue. Furthermore, the negative sign of bid amount makes a sense in that the interest of individuals paying for the resources getting decline as bids amount increased; because income constraint influences individuals’ preferences which comply with demand and supply theory. Distance from forest of interest is the explanatory variable, which negatively and significantly influences their WTP at 1% significance level. Thus, those cooperative members who are living at a distant place from project needs more training and forestry related extension work. As it was expected, the increment
Major comments | Frequency | % |
---|---|---|
Technical and legal support from government side | 65 | 30 |
Close supervision by World Vision Ethiopia to create transparency and avoid corruption | 95 | 43 |
Cooperatives should work on how to attract non members into development activities, and mobilizing cooperative members in forest management activities | 58 | 27 |
Total | 218 | 100 |
Source: survey result, 2012.
in households’ income will positively and significantly influence their WTP and this makes a sense from economic theory point of view. Thus, creating diversified income sources will more encourage community to pay for the management of the project.
The aggregate measure of welfare change for the sample population was 121,491.40 ETB while for the entire population is 277,256.8 ETB per year respectively. The aggregate net welfare estimation remaining after covering both carbon reversal and operation costs amounted to 96,724.80 ETB per year. If the 26% of carbon revenue will be contributed by the community as they expressed in their WTP, the total welfare benefit will add up to 475,354.60 ETB.
Among the various environmental problems encountered by the community, before the onset of the project, deforestation was identified as the most pressing problem followed by soil erosion and climate variability in the study site. However, after project intervention, the community is able to benefit from improved environmental co-benefits and create job opportunities. Thus, frequent and cautious technical and legal support both from government and World Vision is indispensible to ensure sustainable resource management. Moreover, improved environmental condition will also contribute to county’s poverty reduction strategy. Environmental co-benefits should gear towards improving the livelihood of respective community. In this respect, the government should give emphasis to both cooperatives capacity building and environmental rehabilitation efforts to ensure sustainable resources management.
Furthermore, the study result revealed that although the community got environmental co-benefits, there was a conflict between respective community and wild animals. Thus, to overcome the challenge, the community will be enforced to set fire on forest to chase them out of the forest. Moreover, some of the respondents also expressed their concern that the forest will be susceptible to encroachment during prolonged drought reason thus; they might be forced to make charcoal and collect firewood for sale as a copping strategy. Therefore, in order to avert the situation, government should closely work with community on how to overcome the challenge through providing trainings and also look for legal hunting as a means of income sources for the community. Moreover, during crop failure, the government should also provide immediate response or aid support to calm the situation.
Based on the findings of this study, the policy recommendations could be generalized into the following points.
Due to the remarkable effort of the community, the once severely degraded mountain has fully rehabilitated and able to provide ecological and economical benefits to the community. Thus, such a good lessen should be scaled up and scaled out both by governmental and nongovernmental organizations into similar environment.
During the designing of forestry project, conducting of thorough assessment and critical planning in due consideration of the conflict between human being and wild animals. Thus, the government should make some kind of measures/policy decision on how to manage the risk of wild animals to the respective community.
The application of economic valuation techniques found to be important to measure how the people value the environment/ecosystem values expressing their willingness to ensure sustainable forest management. Thus, higher institutions and individual researchers should conduct the economic valuation in similar areas to inform policy makers.
It is better for the government and World Vision Ethiopia to discuss and reach on consensus with community in the modality of benefit sharing from the sale of carbon credit instead of fully reinvesting in common social infrastructure facilities. It is because of lack of common understanding that, those individuals who spent more time in cooperative was hesitated (negatively and significantly react) to pay for the resource management. It is quite clear that, most of infrastructures development is the responsibility of the government. Thus individuals should benefit from the sale of carbon credit to improve their livelihood as well as to ensure sense of ownership.
Creating diversified sources of income will improve the livelihood of local community and consequently increase their contribution (WTP) to manage the forest of interest. Thus, in addition to investing on common infrastructure, cooperatives should work more on creating diversified sources of income at individual level to improved access to credit.
First and foremost, I would like to praise the Almighty GOD for His leading Hands that made me courageous enough to successfully finalize this study. I am extremely grateful for the ongoing support, frequent advice and valuable comments of Dr. Zeleke Ewnetu and Dr. Yemiru Tesfaye Lecturers at Wondo Genet College of Forestry and Natural Resources.
I extend my gratitude to World Vision Ethiopia for financial support and permission for course work. I am also thankful to World Vision Ethiopia staff members, Hailu Tefera, Eshetu Hailu and Daniel Nesibu for their logistical support and tireless advice.
I am indebted to my beloved spouse Emebet Teshome for her day-to-day encouragement, support in data entry and analyses and for her endurance to bear the entire family burden during my engagement in course work. Special thanks also go to my lovely Children, Bontu Shanko, Bethel Elmi, Nemeab Elmi and Dawit Elmi for their endurance during my engagement in course work.
Finally, I am also thankful to all unstated colleagues and Humbo forest development cooperatives administration for their assistance in all circumstances in data collection and providing the related information.
Elmi Nure Negewo,Zeleke Ewnetu,Yemiru Tesfaye, (2016) Economic Valuation of Forest Conserved by Local Community for Carbon Sequestration: The Case of Humbo Community Assisted Natural Regeneration Afforestation/Reforestation (A/R) Carbon Sequestration Project; SNNPRS, Ethiopia. Low Carbon Economy,07,88-105. doi: 10.4236/lce.2016.72009